Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "19"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 19 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 31 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 29 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 19, Node N02:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459846 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -1.200882 -1.826249 -0.956372 0.151811 -0.936588 1.461068 6.236753 8.454585 0.8425 0.6868 0.4877 3.020690 3.271302
2459845 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.495786 -0.928072 -0.484104 1.695043 -0.768438 1.605240 7.323848 7.614743 0.7494 0.7638 0.3695 4.929755 4.846925
2459844 digital_ok 100.00% 100.00% 100.00% 0.00% - - -0.056869 0.065902 0.135737 0.899306 5.145459 11.135287 34.188847 7.540081 0.0291 0.0273 0.0013 nan nan
2459843 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000
2459839 digital_ok 100.00% - - - - - 13.738124 17.977870 84.650706 93.241536 nan nan -29.231224 -30.920487 nan nan nan nan nan
2459838 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.272450 -0.893807 0.993899 0.069297 -0.139436 3.194117 7.156528 3.630022 0.0518 0.0527 0.0052 1.239242 1.226462
2459836 digital_ok - 100.00% 100.00% 0.00% - - nan nan nan nan nan nan nan nan 0.0409 0.0503 0.0051 nan nan
2459835 digital_ok 100.00% 100.00% 100.00% 0.00% - - -1.239793 1.409567 -0.689738 1.898526 2.961686 1.236390 36.828084 0.573209 0.0367 0.0368 0.0066 nan nan
2459833 digital_ok 100.00% 100.00% 100.00% 0.00% - - 2.004020 1.179749 0.782664 0.472749 1.223895 4.594024 13.145043 3.487732 0.0322 0.0367 0.0018 nan nan
2459832 digital_ok 100.00% 0.00% 16.13% 0.00% 100.00% 0.00% -1.934205 -1.345005 1.274581 0.287055 1.052994 1.451497 7.412606 10.623693 0.7481 0.4359 0.5713 2.675212 2.759827
2459831 digital_ok 0.00% 100.00% 100.00% 0.00% - - -0.233977 -0.143151 0.071990 0.032558 -0.680503 -0.017153 -0.647490 -0.154567 0.0324 0.0414 0.0014 nan nan
2459830 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% -1.113685 -1.518016 2.023775 0.547196 0.391939 5.550874 18.401282 14.541125 0.0629 0.0650 0.0109 1.319504 1.307995
2459829 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% -1.248092 -1.193629 1.922742 0.535224 3.829092 4.662891 34.019845 28.999335 0.0477 0.0583 0.0058 27.351713 18.525388
2459828 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.959438 1.065092 -0.653295 6.324351 -0.248794 27.539046 28.735900 11.050499 0.0579 0.0676 0.0111 1.281621 1.257556
2459827 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.566110 1.365986 0.959151 10.693143 26.196793 106.165151 1.151242 0.688447 0.0460 0.0588 0.0064 1.249905 1.246317
2459826 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.909291 -1.160142 -0.916118 -0.695835 -0.283256 5.072301 4.156832 8.296958 0.0462 0.0451 0.0032 1.215725 1.211332
2459825 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.183666 0.577449 -0.508202 1.992259 13.490788 14.940822 3.037780 3.734750 0.0647 0.0601 0.0080 1.189122 1.184848
2459824 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.670900 -0.278602 -0.453716 3.152370 10.528729 12.278389 12.171162 20.819367 0.0590 0.0688 0.0080 0.941179 0.938844
2459823 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.868080 8.704884 -0.910580 13.088749 0.195031 12.019292 1.901549 4.562713 0.0544 0.0669 0.0084 1.245676 1.243031
2459822 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.519999 7.187688 -0.838042 14.027157 3.615855 14.225717 3.507960 3.803382 0.0484 0.0785 0.0083 1.209665 1.199960
2459821 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 1.077068 12.404947 -0.813193 16.974047 2.142796 15.861820 0.256541 -0.058800 0.0638 0.0840 0.0142 1.217891 1.205675
2459820 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.405697 6.179111 -0.928462 19.297483 -1.154145 31.823437 1.103838 2.225520 0.7622 0.6740 0.4373 3.820672 4.874365
2459817 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.006650 11.026438 -0.556059 13.255841 0.997409 23.573381 3.815824 3.977954 0.8094 0.6498 0.5158 3.238131 3.259630
2459816 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -1.032997 6.705938 -1.221880 18.137325 -0.592377 23.273595 13.688536 3.003146 0.8447 0.5921 0.6017 3.187919 3.683836
2459815 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.892833 10.437208 -1.145258 14.712814 -0.631522 24.068558 11.610078 2.212559 0.7990 0.6550 0.5245 3.946545 3.701515
2459814 digital_ok 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 19: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Temporal Discontinuties 8.454585 -1.200882 -1.826249 -0.956372 0.151811 -0.936588 1.461068 6.236753 8.454585

Antenna 19: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Temporal Discontinuties 7.614743 -0.928072 -0.495786 1.695043 -0.484104 1.605240 -0.768438 7.614743 7.323848

Antenna 19: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
19 N02 digital_ok ee Temporal Discontinuties 34.188847 -0.056869 0.065902 0.135737 0.899306 5.145459 11.135287 34.188847 7.540081

Antenna 19: 2459843

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Shape nan nan nan inf inf nan nan nan nan

Antenna 19: 2459839

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Power 93.241536 17.977870 13.738124 93.241536 84.650706 nan nan -30.920487 -29.231224

Antenna 19: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok ee Temporal Discontinuties 7.156528 -0.893807 -0.272450 0.069297 0.993899 3.194117 -0.139436 3.630022 7.156528

Antenna 19: 2459835

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok ee Temporal Discontinuties 36.828084 1.409567 -1.239793 1.898526 -0.689738 1.236390 2.961686 0.573209 36.828084

Antenna 19: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok ee Temporal Discontinuties 13.145043 1.179749 2.004020 0.472749 0.782664 4.594024 1.223895 3.487732 13.145043

Antenna 19: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Temporal Discontinuties 10.623693 -1.934205 -1.345005 1.274581 0.287055 1.052994 1.451497 7.412606 10.623693

Antenna 19: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
19 N02 digital_ok ee Power 0.071990 -0.233977 -0.143151 0.071990 0.032558 -0.680503 -0.017153 -0.647490 -0.154567

Antenna 19: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
19 N02 digital_ok ee Temporal Discontinuties 18.401282 -1.113685 -1.518016 2.023775 0.547196 0.391939 5.550874 18.401282 14.541125

Antenna 19: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok ee Temporal Discontinuties 34.019845 -1.193629 -1.248092 0.535224 1.922742 4.662891 3.829092 28.999335 34.019845

Antenna 19: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok ee Temporal Discontinuties 28.735900 1.065092 -0.959438 6.324351 -0.653295 27.539046 -0.248794 11.050499 28.735900

Antenna 19: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Temporal Variability 106.165151 -0.566110 1.365986 0.959151 10.693143 26.196793 106.165151 1.151242 0.688447

Antenna 19: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Temporal Discontinuties 8.296958 -1.160142 -0.909291 -0.695835 -0.916118 5.072301 -0.283256 8.296958 4.156832

Antenna 19: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Temporal Variability 14.940822 0.577449 0.183666 1.992259 -0.508202 14.940822 13.490788 3.734750 3.037780

Antenna 19: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Temporal Discontinuties 20.819367 -0.670900 -0.278602 -0.453716 3.152370 10.528729 12.278389 12.171162 20.819367

Antenna 19: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Power 13.088749 8.704884 -0.868080 13.088749 -0.910580 12.019292 0.195031 4.562713 1.901549

Antenna 19: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Temporal Variability 14.225717 -0.519999 7.187688 -0.838042 14.027157 3.615855 14.225717 3.507960 3.803382

Antenna 19: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Power 16.974047 12.404947 1.077068 16.974047 -0.813193 15.861820 2.142796 -0.058800 0.256541

Antenna 19: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Temporal Variability 31.823437 -0.405697 6.179111 -0.928462 19.297483 -1.154145 31.823437 1.103838 2.225520

Antenna 19: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Temporal Variability 23.573381 -0.006650 11.026438 -0.556059 13.255841 0.997409 23.573381 3.815824 3.977954

Antenna 19: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Temporal Variability 23.273595 6.705938 -1.032997 18.137325 -1.221880 23.273595 -0.592377 3.003146 13.688536

Antenna 19: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Temporal Variability 24.068558 10.437208 -0.892833 14.712814 -1.145258 24.068558 -0.631522 2.212559 11.610078

Antenna 19: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 19: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
19 N02 digital_ok nn Shape nan nan nan inf inf nan nan nan nan
In [ ]: